Early Cancer Detection & Prognosis through Glycomics

早期癌症检测

• 批准号: 7480452
• 负责人: Milos Novotny
• 金额: $ 37.34万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-08 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7480452
• 关键词: Aftercare; Antibodies; Arts; Bioinformatics; Biological; Biological Markers; Cancer Patient; Capillary Electrophoresis; Class; Clinical; Colon Carcinoma; Complex; Data; Development; Diagnostic; Disease Progression; Disease remission; Evaluation; Excision; Female; Hand; Health; Human; Individual; Isomerism; Laboratories; Lectin; Link; Lung; Malignant Neoplasms; Maps; Measurement; Methodology; Microfluidics; Monitor; Numbers; Ovarian; Patients; Pattern; Pharmaceutical Preparations; Phase; Phase III Clinical Trials; Polysaccharides; Procedures; Process; Prostate; Proteins; Research; Research Personnel; Sampling; Screening for cancer; Screening procedure; Serum; Staging; Structure; Technology; Validation; analytical tool; base; cancer type; clinically relevant; comparative; glycosylation; male; outcome forecast; phase change; prognostic; programs; tool; trend; tumor progression

DESCRIPTION (provided by applicant): Rather than looking for specific cancer biomarkers (proteins or glycosylated proteins), we emphasize quantitative deglycosylation (removal of glycans) in unfractionated biological samples and displaying the removed glycans in quantitative glycan maps. Comparing glycomic profiles originating from healthy and diseased individuals should allow the assignment of structural changes associated with cancer. On the other hand, prognosis or a differential assessment of patients' health then relies on the isotopically-aided quantitative MS measurements of such glycan patterns. In the first two phases of our proposed research, clinically relevant samples will be screened through our well-established procedures while using the state-of- the-art MS-based methodologies and capillary electrophoresis. In Phase 1, the glycomic patterns of human blood serum collected from healthy females and males will be compared to those collected from ovarian, prostate, lung and colon cancer patients. Through bioinformatic and statistical evaluation a list of glycan markers that are associated with each type of cancer or with all types of cancer to be studied will be determined. This is necessary to establish quantitative trends in glycosylation or the occurrence of "glycosylation aberrations" and link these measurements to positively identified glycan structures. Glycomic profiles acquired for the same samples by CE-LIF will aid in determining changes that are due to changes in structural isomers which cannot be determined through MS. In Phase 2, the glycomic maps of human blood serum of cancer before and after treatment with a specific drug will be compared. In this phase, changes in the set of glycans defined in Phase 1 will be closely monitored and their changes as a result of cancer progression or remission will be evaluated. Phase 2 results will confirm or refute the potential glycan structures that will be defined as potential biomarkers in Phase 1. Upon the identification of these specific glycan changes or the set of glycan structures that change as a result of disease progression or remission, the potential of a faster screening approach such as lectin or antibody microarrays will be investigated. This is the aim of Phase 3 of this study which will focus on defining the best analytical tools that could be utilized as diagnostic and prognostic tool.

描述（由申请人提供）：我们不是寻找特定的癌症生物标志物（蛋白质或糖基化蛋白质），而是强调未分级生物样品中的定量去糖基化（聚糖的去除）并在定量聚糖图中显示去除的聚糖。比较健康个体和患病个体的血糖分布应该可以确定与癌症相关的结构变化。另一方面，患者健康状况的预后或差异评估则依赖于对此类聚糖模式的同位素辅助定量 MS 测量。在我们提出的研究的前两个阶段，将通过我们完善的程序，同时使用最先进的基于 MS 的方法和毛细管电泳来筛选临床相关样本。在第一阶段，将从健康女性和男性收集的人类血清的血糖模式与从卵巢癌、前列腺癌、肺癌和结肠癌患者收集的血清进行比较。通过生物信息学和统计评估，将确定与每种类型的癌症或与待研究的所有类型的癌症相关的聚糖标记物列表。这对于确定糖基化或“糖基化畸变”发生的定量趋势并将这些测量结果与已确定的聚糖结构联系起来是必要的。通过 CE-LIF 获取相同样品的糖组图谱将有助于确定由于结构异构体变化而导致的变化，而这些变化无法通过 MS 确定。在第二阶段，将比较特定药物治疗前后癌症人血清的血糖图。在此阶段，将密切监测第一阶段定义的聚糖组的变化，并评估它们因癌症进展或缓解而发生的变化。第 2 阶段的结果将证实或反驳将在第 1 阶段被定义为潜在生物标志物的潜在聚糖结构。在识别出这些特定的聚糖变化或由于疾病进展或缓解而变化的一组聚糖结构后，将研究更快的筛选方法，例如凝集素或抗体微阵列。这是本研究第三阶段的目标，该阶段将重点定义可用作诊断和预后工具的最佳分析工具。